Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments

Autores
de Cristóforis, Pablo; Nitsche, Matias Alejandro; Krajník, Tomáš; Pire, Taihú Aguará Nahuel; Mejail, Marta Estela
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this paper we present a vision-based navigation system for mobile robots equipped with a single, off-the-shelf camera in mixed indoor/outdoor environments. A hybrid approach is proposed, based on the teach-and-replay technique, which combines a path-following and a feature-based navigation algorithm. We describe the navigation algorithms and show that both of them correct the robot's lateral displacement from the intended path. After that, we claim that even though neither of the methods explicitly estimates the robot position, the heading corrections themselves keep the robot position error bound. We show that combination of the methods outperforms the pure feature-based approach in terms of localization precision and that this combination reduces map size and simplifies the learning phase. Experiments in mixed indoor/outdoor environments were carried out with a wheeled and a tracked mobile robots in order to demonstrate the validity and the benefits of the hybrid approach.
Fil: de Cristóforis, Pablo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Nitsche, Matias Alejandro. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Krajník, Tomáš. Czech Technical University In Prague; República Checa
Fil: Pire, Taihú Aguará Nahuel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Mejail, Marta Estela. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
Mixed Indoor/Outdoor Environments
Mobile Robotics
Vision-Based Navigation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/59540
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/59540
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environmentsde Cristóforis, PabloNitsche, Matias AlejandroKrajník, TomášPire, Taihú Aguará NahuelMejail, Marta EstelaMixed Indoor/Outdoor EnvironmentsMobile RoboticsVision-Based Navigationhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2In this paper we present a vision-based navigation system for mobile robots equipped with a single, off-the-shelf camera in mixed indoor/outdoor environments. A hybrid approach is proposed, based on the teach-and-replay technique, which combines a path-following and a feature-based navigation algorithm. We describe the navigation algorithms and show that both of them correct the robot's lateral displacement from the intended path. After that, we claim that even though neither of the methods explicitly estimates the robot position, the heading corrections themselves keep the robot position error bound. We show that combination of the methods outperforms the pure feature-based approach in terms of localization precision and that this combination reduces map size and simplifies the learning phase. Experiments in mixed indoor/outdoor environments were carried out with a wheeled and a tracked mobile robots in order to demonstrate the validity and the benefits of the hybrid approach.Fil: de Cristóforis, Pablo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Nitsche, Matias Alejandro. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Krajník, Tomáš. Czech Technical University In Prague; República ChecaFil: Pire, Taihú Aguará Nahuel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Mejail, Marta Estela. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaElsevier Science2015-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/59540de Cristóforis, Pablo; Nitsche, Matias Alejandro; Krajník, Tomáš ; Pire, Taihú Aguará Nahuel; Mejail, Marta Estela; Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments; Elsevier Science; Pattern Recognition Letters; 53; 2-2015; 118-1280167-8655CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0167865514003274info:eu-repo/semantics/altIdentifier/doi/10.1016/j.patrec.2014.10.010info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:11:01Zoai:ri.conicet.gov.ar:11336/59540instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:11:01.906CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments
title Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments
spellingShingle Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments
de Cristóforis, Pablo
Mixed Indoor/Outdoor Environments
Mobile Robotics
Vision-Based Navigation
title_short Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments
title_full Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments
title_fullStr Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments
title_full_unstemmed Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments
title_sort Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments
dc.creator.none.fl_str_mv de Cristóforis, Pablo
Nitsche, Matias Alejandro
Krajník, Tomáš
Pire, Taihú Aguará Nahuel
Mejail, Marta Estela
author de Cristóforis, Pablo
author_facet de Cristóforis, Pablo
Nitsche, Matias Alejandro
Krajník, Tomáš
Pire, Taihú Aguará Nahuel
Mejail, Marta Estela
author_role author
author2 Nitsche, Matias Alejandro
Krajník, Tomáš
Pire, Taihú Aguará Nahuel
Mejail, Marta Estela
author2_role author
author
author
author
dc.subject.none.fl_str_mv Mixed Indoor/Outdoor Environments
Mobile Robotics
Vision-Based Navigation
topic Mixed Indoor/Outdoor Environments
Mobile Robotics
Vision-Based Navigation
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In this paper we present a vision-based navigation system for mobile robots equipped with a single, off-the-shelf camera in mixed indoor/outdoor environments. A hybrid approach is proposed, based on the teach-and-replay technique, which combines a path-following and a feature-based navigation algorithm. We describe the navigation algorithms and show that both of them correct the robot's lateral displacement from the intended path. After that, we claim that even though neither of the methods explicitly estimates the robot position, the heading corrections themselves keep the robot position error bound. We show that combination of the methods outperforms the pure feature-based approach in terms of localization precision and that this combination reduces map size and simplifies the learning phase. Experiments in mixed indoor/outdoor environments were carried out with a wheeled and a tracked mobile robots in order to demonstrate the validity and the benefits of the hybrid approach.
Fil: de Cristóforis, Pablo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Nitsche, Matias Alejandro. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Krajník, Tomáš. Czech Technical University In Prague; República Checa
Fil: Pire, Taihú Aguará Nahuel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Mejail, Marta Estela. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description In this paper we present a vision-based navigation system for mobile robots equipped with a single, off-the-shelf camera in mixed indoor/outdoor environments. A hybrid approach is proposed, based on the teach-and-replay technique, which combines a path-following and a feature-based navigation algorithm. We describe the navigation algorithms and show that both of them correct the robot's lateral displacement from the intended path. After that, we claim that even though neither of the methods explicitly estimates the robot position, the heading corrections themselves keep the robot position error bound. We show that combination of the methods outperforms the pure feature-based approach in terms of localization precision and that this combination reduces map size and simplifies the learning phase. Experiments in mixed indoor/outdoor environments were carried out with a wheeled and a tracked mobile robots in order to demonstrate the validity and the benefits of the hybrid approach.
publishDate 2015
dc.date.none.fl_str_mv 2015-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/59540
de Cristóforis, Pablo; Nitsche, Matias Alejandro; Krajník, Tomáš ; Pire, Taihú Aguará Nahuel; Mejail, Marta Estela; Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments; Elsevier Science; Pattern Recognition Letters; 53; 2-2015; 118-128
0167-8655
CONICET Digital
CONICET
url http://hdl.handle.net/11336/59540
identifier_str_mv de Cristóforis, Pablo; Nitsche, Matias Alejandro; Krajník, Tomáš ; Pire, Taihú Aguará Nahuel; Mejail, Marta Estela; Hybrid vision-based navigation for mobile robots in mixed indoor/outdoor environments; Elsevier Science; Pattern Recognition Letters; 53; 2-2015; 118-128
0167-8655
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0167865514003274
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.patrec.2014.10.010
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842270142266867712
score 13.13397

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